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When LLM Therapists Become Salespeople: Evaluating Large Language Models for Ethical Motivational Interviewing

arXiv 2503.23566 ↗First posted 30 Mar 2025cs.CLcited by 0

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Abstract (arXiv)

Large language models (LLMs) have been actively applied in the mental health field. Recent research shows the promise of LLMs in applying psychotherapy, especially motivational interviewing (MI). However, there is a lack of studies investigating how language models understand MI ethics. Given the risks that malicious actors can use language models to apply MI for unethical purposes, it is important to evaluate their capability of differentiating ethical and unethical MI practices. Thus, this study investigates the ethical awareness of LLMs in MI with multiple experiments. Our findings show that LLMs have a moderate to strong level of knowledge in MI. However, their ethical standards are not aligned with the MI spirit, as they generated unethical responses and performed poorly in detecting unethical responses. We proposed a Chain-of-Ethic prompt to mitigate those risks and improve safety. Finally, our proposed strategy effectively improved ethical MI response generation and detection performance. These findings highlight the need for safety evaluations and guidelines for building ethical LLM-powered psychotherapy.

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References · 19

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  3. 2023Cognitive Reframing of Negative Thoughts through Human-Language Model Interactioncited by 77
  4. 2023MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Modelscited by 63
  5. 2024A Computational Framework for Behavioral Assessment of LLM Therapistscited by 62
  6. 2023Facilitating Self-Guided Mental Health Interventions Through Human-Language Model Interaction: A Case Study of Cognitive Restructuringcited by 53
  7. 2024HealMe: Harnessing Cognitive Reframing in Large Language Models for Psychotherapycited by 47
  8. 2023Benefits and Harms of Large Language Models in Digital Mental Healthcited by 40
  9. 2023Empowering Psychotherapy with Large Language Models: Cognitive Distortion Detection through Diagnosis of Thought Promptingcited by 31
  10. 2024Risks from Language Models for Automated Mental Healthcare: Ethics and Structure for Implementationcited by 27
  11. 2024Towards a Client-Centered Assessment of LLM Therapists by Client Simulationcited by 24
  12. 2023Helping the Helper: Supporting Peer Counselors via AI-Empowered Practice and Feedbackcited by 23
7 more
  1. 2024Can AI Relate: Testing Large Language Model Response for Mental Health Supportcited by 21
  2. 2024Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contextscited by 19
  3. 2024Virtual Agents for Alcohol Use Counseling: Exploring LLM-Powered Motivational Interviewingcited by 17
  4. 2024Large Language Model for Mental Health: A Systematic Reviewcited by 14
  5. 2024CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapycited by 12
  6. 2024Rethinking the Alignment of Psychotherapy Dialogue Generation with Motivational Interviewing Strategiescited by 10
  7. 2024Unveiling and Mitigating Bias in Mental Health Analysis with Large Language Modelscited by 5

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